A Hybrid Algorithm for Classification of Compressed ECG
Автор: Shubhada S.Ardhapurkar, Ramandra R. Manthalkar, Suhas S.Gajre
Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs
Статья в выпуске: 2 Vol. 4, 2012 года.
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Efficient compression reduces memory requirement in long term recording and reduces power and time requirement in transmission. A new compression algorithm combining Linear Predictive coding (LPC) and Discrete Wavelet transform is proposed in this study. Our coding algorithm offers compression ratio above 85% for records of MIT-BIH compression database. The performance of algorithm is quantified by computing distortion measures like percentage root mean square difference (PRD), wavelet-based weighted PRD (WWPRD) and Wavelet energy based diagnostic distortion (WEDD). The PRD is found to be below 6 %, values of WWPRD and WEDD are less than 0.03. Classification of decompressed signals, by employing fuzzy c means method, is achieved with accuracy of 97%.
Linear Predictive coding, Discrete wavelet transform, Probability Density Function
Короткий адрес: https://sciup.org/15011659
IDR: 15011659
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